MS in Data Science

As data accumulates across broad sectors of industry and academia we see a need for data scientists equipped with skills to assist with data-based decision making. For example, businesses are using data to determine insurance coverage, to make marketing decisions, to offer recommendations to customers, and to provide more effective health care. A famous example from academia is the determination of the Higgs Boson from simulated data with machine learning methods.

We offer a Masters in Data Science degree that covers basic and advanced essentials in statistical inference, machine learning, data visualization, data mining, and big data methods, all of which are key for a trained data scientist. In order to be selected for our program we require a basic background in calculus, linear algebra, probability, computer programming, data structures, and algorithms. Our program is spread across 30 credits and contains projects involving big datasets, classification methods, variable selection, and deep learning to name a few.

In our curriculum, we make extensive use of the Python programming language and its data science libraries while also featuring tools like R for statistical analysis, Tableau for data visualization, and SQL for databases. Students work on assignments covering both theory and applications on real data with support available from the professor and teaching assistant.

Our career services office assists students with resume preparation and reaching out to companies in need of data scientists. While business publications like the Harvard Business Review have written about the lucrative prospects of data science, a search on the career website indeed.com for "data science" reveals a considerable number of opportunities in the New Jersey and New York region.

As described in the curriculum linked below, the program contains two tracks: a Computational Track, and a Statistics Track.

To see the curriculum and degree program requirements, follow this link.